An attention mechanism for content-based filtering of multi-level features. For example, recurrent features obtained by forward and backward passes of a bidirectional RNN block can be combined using attention feature filters, with unprocessed input features/embeddings as queries and recurrent features as keys/values.
Source: NeuriCam: Key-Frame Video Super-Resolution and Colorization for IoT CamerasPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Colorization | 1 | 20.00% |
Key-Frame-based Video Super-Resolution (K = 15) | 1 | 20.00% |
Super-Resolution | 1 | 20.00% |
Total Energy | 1 | 20.00% |
Video Super-Resolution | 1 | 20.00% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |